LaunchPod - Curtis Stevens === Curtis: [00:00:00] the people at Tinder are genuinely trying to create an environment where they can get people to connect with each other. It's not, a hookup app, right? They care very deeply , about their customers, ? But what we started to realize was like. We're a product led company. We're always coming up with new ideas. We're always trying to stay fresh. But we also can't neglect the experience that users are having today, and that's what they're doing. users are leaving the experience they're having today, not the one that you're promising them for tomorrow. Jeff: Welcome to Launch Pod, the show from Log Rocket, where we sit down with top product and digital leaders. Today we're talking with Curtis Stevens, who until recently was Tinder's Director of Product Consumer Insights, and prior to that, held product leadership roles at Qualtrics, Amazon, and more. In this episode, Curtis shares how AI can actually be a tool for human connection. His process behind Tinder's transformation into customer centricity with real measurable results. How to balance short-term user joy with long-term product innovation and future features, and how AI is driving customer experience changes faster than the research can follow, and what you can do to keep up. So here's our episode with Curtis [00:01:00] Stevens. alright, Curtis, good to have you on the show, man. Welcome. Thanks for coming on. Curtis: Thanks. Great to be here. Jeff: I'm excited. We met back in Seattle about six months ago. It's been great, you know, staying in touch, but but now you know, I wanna talk about most recently you were over at Tinder. You came in with really a mandate to help build a culture of customer centricity. We're gonna go into what that looked like and what they meant and how you did that. But maybe before we dive in, can you just give us like the 62nd background of how did you end up there and what took, you know, Curtis Stevens from, you know, beginning a career to where you are now. Curtis: probably most relevant would be going back to my days at Amazon. You know, the first half of my time there was spent in Amazon advertising when it was still very much a startup mode and running program management teams of global program management. And then lastly like an six sig, lean Six Sigma team. And we had to build it from scratch. And I didn't know that much about it other than common sense things you learn in college, right? so I started reaching out to different teams and it turned out the customer experience team [00:02:00] and experience strategy teams had Lean Six Sigma. And so I started working with them and we started developing kaizens. And then I started to realize there's like something to this about learning more about our customers. It's not just. Process improvement, improve. So I wound up meeting one of the directors out there and they brought me in to start working in the experience strategy team. So I became a senior customer experience manager, and my time there was incredible. I learned. talk about customer centricity, right? I learned everything. I went to call centers. I talked to customers, and started developing this approach to journey mapping, which was a derivative of kaizens, but with more customer empathy and more of a voice of customer aspect to it. I watched third party prime and third party sales grow from six customer service agents, to like 135,000 globally and helped build the strategy for that and it was really incredible. But I started wondering if I was a one trick pony, you know? And Qualtrics came knocking on my door and they were like, Hey, maybe you'd like to come over here and start doing this for clients. So I went to [00:03:00] Qualtrics and started, heading up the technology consulting teams there. First as program architect and then as a leader. And started using Journey workshops also internally for us, for even things like how to optimize the source to hire experience and things like that, to make it more equitable, and then a friend of mine and colleague that I worked at Amazon wound up going to Tinder, and we used to meet every other week. And finally I said to him like I'd like to go start my own CX program because I'd done the internal one at Qualtrics. And so he brought me in and it was a greenfield opportunity Tinder felt like they were customer centric, and there was an appetite to learn. Jeff: And so that took us to your most recent role where you came in to into Tinder. I think everyone knows Tinder, right? The dating app you know, swipe less, swipe right. This is all stuff I had to learn actually. 'cause I was married before Tinder was popular, but, so I never used these things and now I was reeducated though before we talked, so, so yeah, I guess you come in you have this push to, help build a more customer centric culture. And I think it all, started. From a point where you gave a like [00:04:00] fateful presentation. I don't know the whole story here, Curtis: yeah I mean, it's kind of an interesting backstory. I came into Tinder and I started listening and learning about the culture and about the mindset of the people at Tinder. I think one thing that a lot of people don't realize is like the people at Tinder are genuinely trying to create an environment where they can get people to connect with each other. It's not, you know, a hookup app, right? Like people actually want people to have relationships and they care very deeply about, about their customers, right? But what I noticed was there was. A lot of disparate data and people were a little reticent to invest in a new approach, so I had to think about like, how do I win these people over? How do I get tendered to see the value of cx? And so, I dug in on journey mapping and journey workshops because I know that's a way to break down information silos and organizational silos, and also get buy-in from everybody in advance. 'cause you, we all know like part of the problem. You're a product person and you've got an idea, you need to talk the engineering team into it. You need to talk the executives into it, and journey workshops are a great way to kind of get all of that lined up and build those [00:05:00] relationships between teams. Jeff: So. If I understand right, you know, 'cause we all witnessed the explosion of the modern, mobile centric dating app. And I think Tinder was the, you know, the leader of the pack there Right. Kinda came out and that was the fir if you say dating apps, know, Tinder is probably one of the top ones that people will say, but you know, with massive growth over time, you start to hit a point where you are so penetrated into the market that, you know, it becomes just you, your denominator of members is so high that a little bit of churn can actually really erode a lot of not, you know, new growth on top. So is that kinda what was going on There was not that there was shrinkage or anything, but more. It's early to kind of, it's easy to ignore CX early on because you can just, a healthy, strong top of funnel covers a lot of sins, but at some point retention becomes just so much more important. And we've had, like Zuora on recently and several other companies that are all talking about now, part of their growth strategy involves. Much heavier push on retention because, you know, LTV values [00:06:00] go up. It just helps your top line, you know, growth numbers 'cause you're not losing as much on the bottom and all these things. But it's really growth through retention becomes important and a great customer experience is huge there. Curtis: It really is. And the sort of generational movement in terms of like your core customer base, you know, the segments of users and everything they're always aging. They're either aging up or aging out, right? And so you have to really keep abreast of some of the changes that are happening in society and how people's communication styles and values change over time. And that was kind of what led to this fateful discussion. You know, I gave a presentation. to the C-Suite executives about the user experience. I was trying to come up with a unique insight, something that would be new and impactful for say, future planning. And one of those things was like you know, we did a bunch of research on the numbers. We were looking at people who weren't reactivating, you know, and customer return is specific and trying to ask ourselves why. And what we started to realize was like. We're a product led company. We're always coming up with new ideas. We're always trying to stay fresh. But we also can't neglect the experience that users are having today, and that's what they're doing. [00:07:00] users are leaving the experience anywhere they're leaving, the experience they're having today, not the one that you're promising them for tomorrow. And so I gave this presentation. We talked about some light numbers, and then at the end we showed them, you know, it was kind of like session replay, but not quite as sophisticated. I wish we'd had that at the time. would've been really useful, you know? But what we did was we showed this first person view a screen recording, and it was, you know, somebody was swiping and they, it was an upsell or did you know how to use this feature? Or do you know that it was a several swipes in before they actually got to a profile. And, the executives just kind of looked at that and they were like, wow, we need to fix that, And the chief product officer, Sarah Rose, and she came up to me and she was like. You know, I want to be your executive sponsor, and that just kind of ex when things kind of exploded, right? Like we a couple weeks later we got to talking. And she's like, I wanna bring you under me and I want you to be the interim director. We'll see how it goes over time, over these three teams, because the three research teams, which was experience strategy, consumer research, and user experience research, they're all located in different [00:08:00] divisions, you know? So there was a lot of overlap. There were opportunities to collaborate that weren't being taken advantage of. Just simple human nature, right? You're busy, and so she gave me the mandate to come in and consolidate these teams into one sort of organism if you will. Jeff: Yeah. No, I mean, and that makes sense. I can see where at one point you wouldn't set up that way, but it intuitively makes sense that those things all overlap heavily. Who, I gotta ask, who were you reporting into when you first joined the company? Where did the position sit then? Curtis: When I was first reporting into the company, I was sitting under underneath trust and safety operations. Which actually great because I got to build really strong relationships with the operators and the agents on the front lines, as well as the trust and safety product and engineering teams. It was very valuable. Jeff: right. But if you're looking at how do we drive the company to being customer, you know, more customer focused and CX led. It feels like a, like you said, Tinder is a product-led company. It's not, there's not a sales team out pushing, you know, you don't have SDRs calling people you don't have. That'd be hilarious actually, if you had SDRs calling people. But it's, people [00:09:00] discover the app and you have to onboard yourself. It's very person-centric like that. And if you want to make this transformation, there's really no other spot You could have been. But under the product banner. 'Cause that's where it's gonna all live. And right. You're gonna need the connections into trust and safety. You're gonna need all those departments you talked about around customer research. But I think this is a good point that to go into, you know, we're gonna go into what actually happened over the time and how you drove this forward. But so many projects like this, I've found just time and time again, if you don't have the right. Structure or the right setup. You're just hobbling yourself from the beginning like you said, people think, oh, you can collaborate, you can go talk to them. Still they're right there. But like you said, people get busy and the first thing to go is sometimes cross team collaboration, but they're all together. And if you know, you kinda have all three that's setting you up for success right from the beginning. Curtis: Oh, a hundred percent. You know, when the reorg happened, there were so many product managers and product designers that were just, they were sending messages. They were just like, oh my God, this makes so much sense. I don't know why we haven't done this before. It was a win, you know? And. And it was a question of how do we get the right research to the right [00:10:00] people at the right time, and how do we snap what we're doing to the product life cycle so that we can do that effectively, Jeff: it also at some level sends, you know, just a. Cultural message to the company. This is important, and we are aligning teams around this goal. Cool. So now you're set for success, right? Like before you had excuse, if it didn't work, you could you know, oh, the teams weren't together. Oh, I didn't have the right executive sponsor. But now you got the CPO, you know, rallying for you and pushing you. You got all the teams you need aligned. What do you do now? What happened after that? For Curtis? Curtis: Yeah, it was, you know, was incredible. So what we what I wound up doing is taking some time and like I went and I spoke with all the executives, you know, and. And try to understand what it was they were trying to gain, what some of the concerns were, what were some of their problems sitting in on their meetings and just learning a lot. And then we came up with like a strategy, which was how do we align these three teams to help the product team as quickly as possible? Right. Yeah, might be a little sticky, but it was like to position research as a proactive strategic force that empowers human insight to business [00:11:00] outcomes, Helping Tinder make bold user-centered decisions that drive growth, innovation, relevance in a rapidly evolving gating landscape, which was pretty much, you know, what we did. And if you think about it. You have three teams experience strategy, which is focusing on building a holistic understanding of the end-to-end customer journey and being able to speak to that customer corner. You know, like every opportunity we have, we are right out there front and center talking about the customer and the journey, then doing that overall touch points, right? And so that gives us those listening posts and help us understand the moments that matter. And bring people together for collaborative discussions. We have consumer research is, which has got a little more longevity to it, right? So like understanding the user per perceptions, attitudes and needs as they evolve over time. And what are their motivations? What are they trying to re really get out of the experience? And then figuring out how to broaden our business strategies, marketing strategies and product development decisions to, to be more tailored around what's coming, like Gen Z, gen Alpha eventually, right? Then user experience research, ? Which is like focusing specifically on the experience that users are having when they're [00:12:00] interacting with Tinder. Not just the products, but the services. And then ensuring that we're easy to, Tinder was easy to use, intuitive, and met the user needs. And to do that, we have to dive in, right? And build those relationships with the product teams. Jeff: And you know. You joined the company August of 2022, so we're not that far removed that point from people being terrified of being with other humans pretty much. Did that play into it all of kind of the opening back up of society? Like was it a good jumping off point at that point to kinda rethink this stuff or? Curtis: Oh, that's endlessly fascinating. I mean, honestly, you know, when I first came into Tinder I thought this isn't that complicated. It's gonna be, you know, I'm gonna get bored, right? And. endlessly fascinating, right? Because, you know, you can do a good job of connecting people and matching or whatever, right? But what happens after that? And you've got a bunch of people who are like huddled up in their houses and walking alone and not really communicating, especially in their formative years, right? As transitioning into adulthood, nobody knows how to talk to each other, And so the sort of interpersonal dynamic was [00:13:00] something that, you know, we started to really lean in on. It's just like, how do we get people connecting and talking with each other? Jeff: I'll be honest, that sounds like a great use for ai, right? You know, everyone talks about now you have people just kind of write, everything's being written by, you know, AI and you know, chat. GBT fuels answers. I saw a commercial or a ad the other day, whereas like two people in like a gas station, a customer in a cashier, and it was like the cashier. Said hello to me. What do I say? And then, you know, it went back and forth, but like, in reality, that might actually help. At least some people I've known who did Tinder. It's like, well, I think I know why you're not getting past that first little bit of conversation. You, you sound insane. Maybe tighten it up and like, you know, that'd be a good use case there. Like, don't, do you really wanna say that? Is that really your answer right now? Curtis: And that's kind of exactly where things are kind of headed. Like, I mean, I have some personal thoughts on this that I've nothing to do with the Tinder strategic roadmap, right? But like, you know, imagine a realm where, you know, you've got what do you call it, like a sidekick or a wing person Jeff: yeah. That's what you got the branding for right [00:14:00] there. It's, you call it, you know, wing per wing person. Curtis: Yeah. Or a matchmaker who's like, hey, Jeff. I noticed that, you know, you and Mary have like a ton in common, you know, like, you know, they recently posted that they're going to a concert and they're super excited about it. Have you been to one? You know, and then it starts getting that, you know, just kicking off that conversation to get people more warm and comfortable and running introductions and, you know, maybe in real time even just like helping you out with messaging. Like really, you know, like maybe forego the fish pick, you know. Jeff: It's great because, I mean, I think it shows the cultural permutation that Tinder and apps like that had because. Like I said, I was, if not married, I was already like, well into a relationship with the person who became my spouse by the time Tinder even, you know, came out. But all these things it's not just a dating app, it's pop culture references, right? Like the Phish pick you know, swipe right. All these things are things that transcend. Dating apps. And so that, you know, kinda goes back to right, the importance of the customer experience around that because there are certain [00:15:00] things that people expect, but there's also certain things people see as negatives and how do you build in the handset experience without losing some of those things that are culturally important, deeper at some level than even just user experience, but like culturally important across you know, millions of people. Curtis: Yeah. I agree. And how do you use that as a means for connecting people in a way that they're gonna feel comfortable and safe and empowered? that one's gonna go on for a very long time. I think Jeff: yeah. No, I mean, this seems like a place where, there's a lot of opportunity around, you know, morphing it forward, but maintaining that. But I think it's a lost opportunity there. If there's no AI agent named Wingman or Wing person or Wingwoman pretty shortly I just feel like that's a lost opportunity. Okay. So. We're at this point where you have the structures upright and you have the ability to do the research. I guess, can we go into a little bit what did you uncover? Like can we talk about some examples that, you know, actually caused you know, changes in how Tinder approached things? Curtis: There a few things. One, I guess is just speaking very pragmatically, right, [00:16:00] is one is like, is going through and consolidating the three teams onto a common roadmap of the common intake process and really sussing out what kind of problems. We're trying to solve, And I think problem identification is one of the biggest struggles, especially with a young workforce, learning how to think very critically about things. Is really trying to understand what it is you're trying to accomplish. You know, if you wanna do, you know, for instance the women's experience is extremely important at Tinder, right? And so one of our first journey workshops was around new user experience for women days are out the. Seven, which is very critical, right? That first week you're on the app. It's really important to have that good experience. And that was when we started introducing sort of like how do we can gather up all these improvement opportunities and we can ideate about how do we go about like stack ranking them and how do we go about determining what the most important things are to action on? And that was when we, the first one was when we learned it's really important to have. Executive buy-in on the ideas that are coming out of it. And what's kind of funny is like, each time we did one of these workshops, we learned something else. And oddly it just led to the next one. Like it was just this [00:17:00] series of workshops, right? Like, the new user experience for women days zero through seven, we. Notice that bots and bad actors were much more prevalent than we would've liked, right? And so, going in and identifying some AI companies that can help us better identify and tag these bots and bad actors way ahead of time, so that the agents aren't being overwhelmed so that we're protecting the women's experience. Because if the women don't feel safe. You know, they're not gonna stay on your app. Jeff: that's really interesting. So kind of starting with even. The, you know, some of the actions around building a great customer experience didn't even have to do with, you know, new features or anything. But it's also these other things that you don't even that you don't see as a, you can't just go through the onboarding flow and using a UX analytics tool because it won't capture these things. this kinda gets to the point. You brought, these teams need to be together, right? Because some of this derives from what are people concerned about? And you need to talk to people. Some of this derives from analyzing where people are running into friction in the app itself, and bringing this all together gives you the holistic ability to kind of prioritize. Without that, though, you're probably gonna go after problems you're trying to fix [00:18:00] that they're important, but maybe in reality, like the number eight problem and you're treating it like the number one or two. Curtis: A hundred percent. And also minor things, right? Like, like, okay, you know, it's a company we're trying to make money, you know, when is the most appropriate time to upsell somebody? You know, like, honestly, I think Hinge has one of the best approaches to feedback outing I've seen in a long time. There. Their CX team out there is brilliant. You know, Emily runs it. But , one of the things that they do that's really unique is like. You know, they've got this notion of roses, right? That's their soft version. Who doesn't like a rose? Right? And roses are incredibly useful. What happens is users use one, they get the attention of the person they're trying to get, you know, starts a conversation, but you only get one a month or something like that if you're, you know, a free user or on the lower tier, And so what happens is, Hinge is like, ah, that worked. You know, like you're starting to get hits, you know, and that's when they're asking you like, Hey, would you like to get a couple more roses? And we're like, yeah. You know, because they proved the value to you by helping you accomplish what you want, [00:19:00] which is a connection, you know? Jeff: It's a swipe right for dopamine, right? Curtis: and it completely lines up with the journey. Like, yeah. That was pretty successful. I wouldn't mind getting a couple more of these, you know? And then the postdate feedback mechanism, it's like, Hey, how was that date? Did you guys meet in real person? Are you gonna see them again? You know, like, do you wanna take them off your list? And what that does is the company now understands the success rate of. You know what you're trying to accomplish, which is meeting somebody you know, value and someone you can connect with. And they also understand when it doesn't work out that way, so that they can start to think about how to get you matched up with the right people at the right time. You know, really smart. And that stuff comes from journey workshops and talking with your customers and trying to understand. And so. That was kind of what the path we were going down with Tinder at the time was like, okay, well when is the right time? Like how often should we be bombarding somebody? You wouldn't know that without a first person view Jeff: it's interesting because. One of the benefits I've had from doing this podcast and, you know, being able to travel the country and host, you know, product leaders all over in the, you know, like where we met at dinner in Seattle has been hearing kinda these [00:20:00] problems. And one thing I've noticed is cross industry. You run into exactly the thing you just talked about. There is data from, tools you're using to monitor in app. I will plug, you know, things like Log Rocket, which do you know, session replay and how do you intelligently surface that. And now we use AI to watch the sessions for you and surface it all up. It's more than that, right? It is. You are having customer conversations to understand that, like the piece you said about how do people feel safe and where is that important? You have kind of journey maps you have. I mean, in Tinder's case, in most dating apps, I would wager like even if you look at, you know, the Apple Review apple App Store Review Center there's gonna be a lot of great feedback in something like that where people are saying what angered them and why they didn't use the app anymore or something like that. Going through all that is, is a huge lift. ~And that's, you know, selfishly I'm happy that we're trying to solve this problem and we have a product launching around exactly that. Basically like take all that, aggregate it intelligently using ai, tie it to session replay. But you know, that, that comes from the same customer centricity kind of idea of we, we went and talked to customers, we saw what people were frustrated with, we watched what they were trying to do in the app and what would make it better.~ And so, you know, we're B2B analytics software. Tinder is probably the farthest thing I can think of from B2B analytics software and that it's sexy and it's cool and it's hip, and analytics is, you know, not those things. But it's the same problem set Curtis: Yeah, it is. It is the [00:21:00] same problem set. And I think that's a really important thing to think about, right? Is like, you know, tool tools like Log Rocket. It's not just a B2B tool, right? Like it, it really is designed to help us better understand our users, better, understand the impact business impact certain decisions are having, and then getting that fresh first person view so that you can have a conversation, right? It's like stories, it's storytelling. You know, I wanna be able to tell a compelling story. I wanna be able to say, if I'm in retail, right, I want to be able to say that when a person has this kind of negative experience, right? How does that impact their purchase behavior or their searching behavior, their activity levels, right? Once you understand that there's like a financial impact to that experience, and you can start having, telling a story and having a more holistic conversation around what to do with that. Jeff: exactly. And so, you know, maybe to switch topics slightly here but to stand the general macro topic, right? Like a big, a big impact to this work really. I feel like, has come in the past, you know, two years and really accelerated in the past, you know, six, nine months where AI is taking what teams like yours could do before. And there was just so much like [00:22:00] manual work and manual aggregation and just really like izing the whole thing. And this has been something you've talked about quite a bit actually is you can basically do the research faster. Than ever before, but almost faster than that. You can keep up with, and at least some risk and some really interesting insights. And some challenges. And some benefits. Maybe let's pivot to, for leaders who are looking at a program like this, you know, how can they be looking at ai? What is the stuff they need to think about from a cautionary sense? What's the, they should lean into, like, how do you look at this stuff? Curtis: I think it's a few things, right? One is like, from an ethical standpoint is trust but verify, ? Like AI is bionic. I mean, it is absolutely incredible. You know, I had situations where like my model was like. I was like, Hey, I need some customer quotes around this user experience. And it gave me a bunch of really great ones. And then I went and searched for them, and there it was. I was like, oh, yeah. Not representative contacts, right? Like, I need actual customer, you know? And so. Jeff: the third person I've talked to in the past 24 hours who mentioned that specific thing, like [00:23:00] gimme sources, cite them, and then going, I don't think you just made that up, didn't you? And it's like, yeah, I My bad. Curtis: yeah. It's like, right, like anybody who's used, you know, chat GBT to write a resume, right? Like, like all of a sudden there's, it somehow it just works in a bunch of stuff that it thinks you should have done, you know? And it's like, you know, so like, it's the same thing Jeff: That's totally what I'm gonna, if I ever do use Tinder, by the way, that's totally what I'm going to blame it on. I'm six five and then, oh, the a, the AI just, I don't know, that's hallucination. I don't know where that came from. I'm blame, I'm totally just blaming, blame the AI for anything like that. It put the fish picture there. It, Curtis: Yeah. Yeah. so, starter, right? But you know, to me it's like trust with verify. It's it's also like, I think we were talking at one point about like, you know, voi stitching the data together. Voice of customer, voice of agent, voice of process, voice of business. And if you can start to tie those things together, you know, you'll figure out the hallucinations a lot more quickly. But in terms of speed to insights, if the closer you can get that data married. To create a view and tell a story, the faster you're going to be able to make these decisions, or at [00:24:00] least feel a stronger degree of confidence that you're solving the right problem. Right? I would say the other one is experimentation, right? Like, a lot of companies that I've seen, you know, they're leveraging, I, they're getting these insights, they're modeling the results. Their approach to experimentation is like, you know, they get nervous, right? You launch something, you try it out and it doesn't go the way you thought or the, it's affecting the wrong KPIs, is it? Just take a minute and don't question the, necessarily the experiment, ? But how effectively are you launching these experiments and how effectively are you learning and then iteratively improving whatever it is you want to focus on. I think that's really key, is like how are we using this data? How are we executing at the end? Jeff: And I think, right, that's a good point you bring up is kind of. It's still AI or not, it comes down to we're, you know, software is just the means to the end. Software is not the actual thing. The actual thing for Tinder, right, is, like you said it's human connection. Jeff: For Log Rocket, it's insights into how users are experiencing your digital product. AI doesn't change that. It just, accelerates your ability to move forward. It allows you to process bigger context windows. But it is just like [00:25:00] avoid you know, avoid the what we talk a lot here about operational failure and experimental failure and right, like experimental failure is just, you tried something, you had a good hypothesis. It just doesn't work. Like sometimes just things just don't work. It's just you were wrong. And then operational failure is, you don't know if you're right or wrong, you just didn't do the thing right. And I feel like that's something I always keep in mind and that AI can very much help with is as you're parsing through like why something failed and then you start to look at feedback. You look at how it was run to your point or how you ran a thing. It can really help you first get into, validate some of those things and understand why. And you can start to see like, can we trust this or do we just need to throw the whole thing out? Curtis: why is the key point, right? Like a lot of times, you know, if you're trying to move fast people aren't taking the time to actually ask why didn't this work exactly. You know, wrong market, wrong treatment, you know, even minor changes in the. the user experience can have dramatic results, you know? And how quickly can you recover from it? Some, sometimes it's a good I mean, I see ideas boomerang all the time and you know, it is easy to kind of roll your eyes and be like, oh God, not this again. But the reality is like. Yeah, the boomerang actually makes a [00:26:00] certain degree of sense. If you're like, I, this is a, we're onto something. We need to experiment with this more. How do we get this rapid prototyping and experimentation that's not disruptive to the overall experience. Jeff: no, it's interesting because like, I mean, to the point you made about Hinge, right? Like a small tweak there, pe you know, if you took away people like roses and you try just to upsell them on Rose, oh hey, you gave a rose away and now you're outta roses. Do you wanna move to paid to, to get more? If you didn't get an answer, if you had a, you know, no positive reaction to the one you did, you're probably not going to. But if you focus more on, like you said, the people who had a positive reaction from that and it drove some kind of interaction, you're likely gonna see a lot more. And, but that's a pretty small tweak in execution, but it's about the why. The why is that important is what really is the lever. So I guess looking at that, did you find ways to kinda reduce those hallucinations or kind of, you know, as you're kind of going through and getting the pieces that, you know, you want tight proof points because sometimes you just want directional accuracy, right? Like, what are the big themes? It's not gonna make up usually giant themes outta nothing but like, quotes and stuff like that. It will, so, you know, I guess you found ways to kind of get, you know, [00:27:00] drive accuracy where you need it and drive speed and breath Curtis: I wish they were more sophisticated. You know, like earlier on in my career I was an auditor at an IT auditor at Deloitte, right. And I learned everything that you could think about for like sampling and frameworks. And so for me, I do I do a lot of like quick gut checks with the numbers, right? Like, I'm a numbers person. I can stare at all. I don't even, I don't like graphs. I could stare an entire wall of any kind of measures and. Find patterns that might take someone else a little bit longer, When I see a pattern, a disruption in the sound or the rhythm, I'm immediately drawn to it. Right. And it's the same thing when you're running experimentation is like. What were the results? Did we run long enough? What were the results? And how closely did the results resemble what you were expecting to see? And then asking why? Why am I seeing something different, you know? Jeff: Why is usually a pretty good question. Almost all cases, why did this work? Why does it not work? Why is this different than I expect? And I found is again, talking to just several leaders across several different verticals and different companies in the same vertical. [00:28:00] That seems to be something that people come back to a lot is, you know, it can help you move faster, but you gotta understand. The details behind it, and you gotta kind of make sure you're using it in the right tools in the right place. But the pace we can move at with CX research now is just so, so much fashion than ever before. Use it for good, use it to create, you know, things like better ways to give out roses or other kind of great human interactions. Not, you know, don't misuse it and just, you know, get nothing valuable. Curtis: Big in small ways, right? Like I think that's really key. I, to me, AI is an incredible tool for bringing people together. It's an incredible tool for synthesizing what you need in a way that is digestible and easy to interpret and easy to have a conversation about. I'm gonna get a teacher that says, why guy? I think, Jeff: There you go. Well, Curtis, this was great man. Thank you so much for coming on. Great to hear, you know, at Tinder, how do you go from. coming in and saying there's a mandate to, to grow CX into really driving a CX culture and, creating a better more enjoyable app to use that, that people can move forward [00:29:00] with that they feel comfortable with, that they get what they want out of, so that you keep your users longer, they refer more, you get more people to use it and just grow faster. And then AI and how it affects it is gonna be really interesting going forward. If people wanna pick your brain more in any of these topics or wanna reach out or, you know, have thoughts is LinkedIn the best place to reach or is there a better way? Curtis: Yeah, either LinkedIn or email works, at least for starters. Yeah. I always down to have a conversation around this. I'm very excited about research and the human experience. Yeah, you can reach me at stevens.Curtis@gmail.com. That's my personal email or LinkedIn is fine as well, you Jeff: Yeah. Curtis: and Jeff, it's a real pleasure. Thank you. Jeff: Thank you for coming on. This is a blast and I hope to see you next time we're in Seattle. Curtis: Alright. Awesome. Thank you so much. Have a good one. thank you. You too. Bye.